Ajmal Hinas
Papers
2
Total Citations
21
H-Index
2
About
Ajmal Hinas is a researcher at the forefront of autonomous aerial robotics, specializing in vision-based navigation and multi-target tracking for multirotor unmanned aerial vehicles (UAVs). His work focuses on developing robust frameworks that enable small drones to autonomously find, inspect, and interact with multiple ground targets—a capability with profound implications for surveillance, wildlife ecology, and environmental monitoring. In his most-cited paper (2020, 12 citations), Hinas introduced a comprehensive framework for multiple ground target finding and inspection, leveraging advanced waypoint-based navigation to allow UAVs to remotely sense targets, descend, and hover for detailed action. His earlier foundational work (2018, 9 citations) established a vision-based position estimation technique, enabling drones to detect and track targets while building an internal map of their relative locations. These contributions have laid critical groundwork for autonomous drone operations in complex, unstructured environments. Hinas’s research stands out for its practical integration of computer vision and control systems, directly addressing real-world challenges in remote sensing and precision inspection. His work continues to influence the next generation of intelligent aerial systems, making him a key figure in advancing UAV autonomy.
Research Focus
Key Achievements
Top Papers
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